Feature scaling strategy for many feature with very large variation between them?
You should check the distribution of each feature and scale them accordingly, but in any case you should aim to roughly the same interval of values for every feature.
For example, if f1 has the standard distribution and f2 is close to the uniform one, then you can scale f1 to N(0,1) and f2 to U(-1,1).
In other words, try to have maximum, minimum and mean values for all features as close as possible, while keeping their original distributions.